Development Analytics & Data Hosting & Cloud

Databricks

Databricks is a cloud lakehouse platform that brings large-scale data engineering, analytics, governance, and machine learning into one managed workspace.

Runs on Web

Available on Web

Built for Startups Enterprise Developers

Overview

What is Databricks?

Where it fits

Databricks is built for teams that want data engineering, SQL analytics, machine learning, and generative AI work in one cloud workspace. It is strongest when large datasets, Spark workloads, and governed collaboration matter more than simple dashboarding.

Working in the lakehouse

Notebooks support SQL, Python, Scala, and R, while jobs turn exploratory code into scheduled pipelines. Delta Lake supplies reliable table storage, and Unity Catalog centralizes permissions, lineage, and discovery across workspaces.

Connect cloud object storage and external databases.
Train, track, register, and serve machine-learning models.

How billing behaves

Paid usage is metered in Databricks Units, with rates varying by workload and cloud. The underlying AWS, Azure, or Google Cloud compute bill may be separate. A free edition suits learning and small experiments, but production costs depend heavily on cluster size, runtime, autoscaling, SQL warehouse choice, and how promptly idle resources shut down.

Capabilities

Key features

Unify data workloads

Run ETL, SQL, machine learning, and AI together

Govern shared assets

Control access and lineage through Unity Catalog

Build reliable pipelines

Schedule notebooks and production data workflows

Track model lifecycles

Manage experiments, registries, evaluation, and deployment

Keep exploring

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